{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T22:52:04Z","timestamp":1785365524033,"version":"3.55.0"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2020,11,8]],"date-time":"2020-11-08T00:00:00Z","timestamp":1604793600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,11,8]],"date-time":"2020-11-08T00:00:00Z","timestamp":1604793600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","award":["NRF-2019R1A2C1006159"],"award-info":[{"award-number":["NRF-2019R1A2C1006159"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"crossref","award":["22A20130012814"],"award-info":[{"award-number":["22A20130012814"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1007\/s12652-020-02654-z","type":"journal-article","created":{"date-parts":[[2020,11,8]],"date-time":"2020-11-08T09:07:07Z","timestamp":1604826427000},"page":"9375-9385","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Extensive hotel reviews classification using long short term memory"],"prefix":"10.1007","volume":"12","author":[{"given":"Abid","family":"Ishaq","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6015-9326","authenticated-orcid":false,"given":"Muhammad","family":"Umer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad Faheem","family":"Mushtaq","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlo","family":"Medaglia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hafeez Ur Rehman","family":"Siddiqui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arif","family":"Mehmood","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gyu Sang","family":"Choi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,11,8]]},"reference":[{"key":"2654_CR1","doi-asserted-by":"publisher","unstructured":"Ajesh F, Ravi R, G R, (2020) Early diagnosis of glaucoma using multi-feature analysis and dbn based classification. J Ambient Intell Hum Comput https:\/\/doi.org\/10.1007\/s12652-020-01771-z","DOI":"10.1007\/s12652-020-01771-z"},{"key":"2654_CR2","unstructured":"Bahdanau D, Cho K, Bengio Y (2014) Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:14090473"},{"issue":"2","key":"2654_CR3","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1109\/72.279181","volume":"5","author":"Y Bengio","year":"1994","unstructured":"Bengio Y, Simard P, Frasconi P (1994) Learning long-term dependencies with gradient descent is difficult. IEEE Trans Neural Netw 5(2):157\u2013166","journal-title":"IEEE Trans Neural Netw"},{"key":"2654_CR4","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010950718922","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L (2001) Random forests. Mach Learn 45:5\u201332. https:\/\/doi.org\/10.1023\/A:1010950718922","journal-title":"Mach Learn"},{"key":"2654_CR5","doi-asserted-by":"publisher","unstructured":"Catal C, Nang\u0131r M (2016) A sentiment classification model based on multiple classifiers. Appl Soft Comput 50. https:\/\/doi.org\/10.1016\/j.asoc.2016.11.022","DOI":"10.1016\/j.asoc.2016.11.022"},{"key":"2654_CR6","doi-asserted-by":"publisher","unstructured":"Chen T, Xu R, Wang X (2016) Improving sentiment analysis via sentence type classification using bilstm-crf and cnn. Expert Syst Appl. https:\/\/doi.org\/10.1016\/j.eswa.2016.10.065","DOI":"10.1016\/j.eswa.2016.10.065"},{"key":"2654_CR7","unstructured":"Chung J, G\u00fcl\u00e7ehre \u00c7, Cho K, Bengio Y (2014) Empirical evaluation of gated recurrent neural networks on sequence modeling. CoRR abs\/1412.3555, http:\/\/arxiv.org\/abs\/1412.3555,"},{"key":"2654_CR8","unstructured":"Collobert R Weston J Bottou\u00a0L KMKK, Kuksa (2011) Natural language processing (almost) from scratch. J Mach Learn Res pp 2493\u20132537"},{"key":"2654_CR9","doi-asserted-by":"publisher","first-page":"38287","DOI":"10.1109\/ACCESS.2019.2907000","volume":"7","author":"S Dai","year":"2019","unstructured":"Dai S, Li L, Li Z (2019) Modeling vehicle interactions via modified lstm models for trajectory prediction. IEEE Access 7:38287\u201338296","journal-title":"IEEE Access"},{"key":"2654_CR10","doi-asserted-by":"crossref","unstructured":"Du J, Vong CM, Chen CP (2020) Novel efficient rnn and lstm-like architectures: Recurrent and gated broad learning systems and their applications for text classification. IEEE Trans Cybern","DOI":"10.1109\/TCYB.2020.2969705"},{"key":"2654_CR11","doi-asserted-by":"crossref","unstructured":"Freire-Obreg\u00f3n D, Castrill\u00f3n-Santana M, Barra P, Bisogni C, Nappi M (2020) An attention recurrent model for human cooperation detection. Comput Vis Image Understand, 102991","DOI":"10.1016\/j.cviu.2020.102991"},{"key":"2654_CR12","doi-asserted-by":"crossref","unstructured":"Freund Y, Schapire RE (1997) A decision-theoretic generalization of on-line learning and an application to boosting. J Comput Syst Sci 55(1):119\u2013139. 10.1006\/jcss.1997.1504, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S002200009791504X","DOI":"10.1006\/jcss.1997.1504"},{"key":"2654_CR13","doi-asserted-by":"publisher","unstructured":"Friedman J (2000) Greedy function approximation: a gradient boosting machine. Ann Stat 29: https:\/\/doi.org\/10.1214\/aos\/1013203451","DOI":"10.1214\/aos\/1013203451"},{"key":"2654_CR14","doi-asserted-by":"publisher","unstructured":"Garcia-Pablos A, Cuadros M, Linaza M (2015a) Automatic analysis of textual hotel reviews. Inf Technol & Tourism 16: https:\/\/doi.org\/10.1007\/s40558-015-0047-7","DOI":"10.1007\/s40558-015-0047-7"},{"key":"2654_CR15","doi-asserted-by":"crossref","unstructured":"Garcia-Pablos A, Cuadros M, Linaza M (2015b) OpeNER: Open Tools to Perform Natural Language Processing on Accommodation Reviews, pp 125\u2013137. 10.1007\/978-3-319-14343-910","DOI":"10.1007\/978-3-319-14343-9_10"},{"key":"2654_CR16","doi-asserted-by":"crossref","unstructured":"Ghorpade T, Ragha L (2012) Featured based sentiment classification for hotel reviews using nlp and bayesian classification. In: 2012 International Conference on Communication, Information Computing Technology (ICCICT), pp 1\u20135","DOI":"10.1109\/ICCICT.2012.6398136"},{"key":"2654_CR17","unstructured":"Gotz M, Weber C, Bl\u00f6cher J, Stieltjes B, Meinzer HP, Maier-Hein K (2014) Extremely randomized trees based brain tumor segmentation"},{"key":"2654_CR18","doi-asserted-by":"crossref","unstructured":"Hand DJ (2013) Data Mining Based in part on the article \u201cData mining\u201d by David Hand, which appeared in the Encyclopedia of Environmetrics., American Cancer Society. 10.1002\/9780470057339.vad002.pub2, https:\/\/onlinelibrary.wiley.com\/doi\/abs\/10.1002\/9780470057339.vad002.pub2,","DOI":"10.1002\/9780470057339.vad002.pub2"},{"key":"2654_CR19","doi-asserted-by":"crossref","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural comput pp 1735\u20131780","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"2654_CR20","doi-asserted-by":"publisher","unstructured":"Huang JS, Chen BQ, Zeng NY, Cao XC, Li Y (2020) Accurate classification of ecg arrhythmia using mowpt enhanced fast compression deep learning networks. J Ambient Intell Human Comput. https:\/\/doi.org\/10.1007\/s12652-020-02110-y","DOI":"10.1007\/s12652-020-02110-y"},{"key":"2654_CR21","doi-asserted-by":"crossref","unstructured":"Hwang SY, Lai C, Jiang JJ, Chang S (2014) The identification of noteworthy hotel reviews for hotel management. Proceedings - Pacific Asia Conference on Information Systems, PACIS 2014 6, 10.17705\/1pais.06402","DOI":"10.17705\/1pais.06402"},{"key":"2654_CR22","doi-asserted-by":"publisher","first-page":"21932","DOI":"10.1109\/ACCESS.2020.2969041","volume":"8","author":"Z Imtiaz","year":"2020","unstructured":"Imtiaz Z, Umer M, Ahmad M, Ullah S, Choi GS, Mehmood A (2020) Duplicate questions pair detection using siamese malstm. IEEE Access 8:21932\u201321942","journal-title":"IEEE Access"},{"key":"2654_CR23","unstructured":"Jason Liu (2017) 515K Hotel Reviews Data in Europe. https:\/\/www.kaggle.com\/jiashenliu\/515k-hotel-reviews-data-in-europe. Accessed 19 Feb 2020"},{"key":"2654_CR24","unstructured":"Joachims T (1999) Making large scale svm learning practical. Advances in Kernel Methods: Upport Vector Machines 10.17877\/DE290R-5098"},{"key":"2654_CR25","doi-asserted-by":"crossref","unstructured":"Kalchbrenner\u00a0N GE, P B (2014) A convolutional neural network for modelling sentences. arXiv preprint arXiv:14042188","DOI":"10.3115\/v1\/P14-1062"},{"key":"2654_CR26","first-page":"96","volume":"4","author":"W Kasper","year":"2012","unstructured":"Kasper W, Vela M (2012) Sentiment analysis for hotel reviews. Speech Technol 4:96\u2013109","journal-title":"Speech Technol"},{"key":"2654_CR27","doi-asserted-by":"crossref","unstructured":"Li J, Luong T, Jurafsky D, Hovy E (2015) When are tree structures necessary for deep learning of representations? In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Lisbon, Portugal, pp 2304\u20132314, 10.18653\/v1\/D15-1278, https:\/\/www.aclweb.org\/anthology\/D15-1278","DOI":"10.18653\/v1\/D15-1278"},{"key":"2654_CR28","doi-asserted-by":"crossref","unstructured":"Long T (2019) Research on application of athlete gesture tracking algorithms based on deep learning. J Ambient Intell Human Comput pp 1\u20139, 10.1007\/s12652-019-01575-w","DOI":"10.1007\/s12652-019-01575-w"},{"key":"2654_CR29","unstructured":"Mandelbaum A, Shalev A (2016) Word embeddings and their use in sentence classification tasks. ArXiv abs\/1610.08229"},{"key":"2654_CR30","unstructured":"Mathieu C (2017) Bb\\_twtr at semeval-2017 task 4: Twitter sentiment analysis with cnns and lstms. arXiv preprint arXiv:170406125"},{"key":"2654_CR31","unstructured":"Mccallum A, Nigam K (2001) A comparison of event models for naive bayes text classification. Work Learn Text Categ 752"},{"key":"2654_CR32","unstructured":"Mikolov T, Sutskever I, Chen K, Corrado G, Dean J (2013) Distributed representations of words and phrases and their compositionality. Adv Neural Inf Process Syst 26"},{"key":"2654_CR33","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1016\/j.eswa.2017.02.002","volume":"77","author":"A Oscar","year":"2017","unstructured":"Oscar A, Ignacio CP, Fernando SRJ, A IC, (2017) Enhancing deep learning sentiment analysis with ensemble techniques in social applications. Expert Syst Appl 77:236\u2013246","journal-title":"Expert Syst Appl"},{"key":"2654_CR34","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D, Brucher M, Perrot M, Duchesnay E, Louppe G (2012) Scikit-learn: Machine learning in python. J Mach Learn Res 12"},{"key":"2654_CR35","doi-asserted-by":"crossref","unstructured":"Pennington J, Socher R, Manning C (2014) Glove: Global vectors for word representation. vol\u00a014, pp 1532\u20131543, 10.3115\/v1\/D14-1162","DOI":"10.3115\/v1\/D14-1162"},{"key":"2654_CR36","doi-asserted-by":"crossref","unstructured":"Potgieter M, de Jager JW, van Heerden NH (2013) An innovative marketing information system: A management tool for south african tour operators. Procedia - Social and Behavioral Sciences 99:733\u2013741. 10.1016\/j.sbspro.2013.10.545, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1877042813039906, the Proceedings of 9th International Strategic Management Conference","DOI":"10.1016\/j.sbspro.2013.10.545"},{"key":"2654_CR37","doi-asserted-by":"crossref","unstructured":"Raut V, Londhe D (2015) Opinion mining and summarization of hotel reviews. Proceedings - 2014 6th International Conference on Computational Intelligence and Communication Networks, CICN 2014 pp 556\u2013559, 10.1109\/CICN.2014.126","DOI":"10.1109\/CICN.2014.126"},{"key":"2654_CR38","doi-asserted-by":"crossref","unstructured":"Richardson A (2011) Logistic regression: A self-learning text, third edition by david g. kleinbaum, mitchel klein. Int Stat Rev79:296, 10.2307\/41305046","DOI":"10.1111\/j.1751-5823.2011.00149_22.x"},{"key":"2654_CR39","doi-asserted-by":"crossref","unstructured":"Rush AM, Harvard S, Chopra S, Weston J (2017) A neural attention model for sentence summarization. In: ACLWeb. Proceedings of the 2015 conference on empirical methods in natural language processing","DOI":"10.18653\/v1\/D15-1044"},{"key":"2654_CR40","doi-asserted-by":"crossref","unstructured":"Sadiq S, Mehmood A, Ullah S, Ahmad M, Choi GS, On BW (2020) Aggression detection through deep neural model on twitter. Fut Gen Comput Syst","DOI":"10.1016\/j.future.2020.07.050"},{"issue":"11","key":"2654_CR41","doi-asserted-by":"publisher","first-page":"1457","DOI":"10.1109\/TKDE.2006.180","volume":"18","author":"Sang-Bum Kim","year":"2006","unstructured":"Kim Sang-Bum, Han Kyoung-Soo, Rim Hae-Chang, Myaeng Sung Hyon (2006) Some effective techniques for naive bayes text classification. IEEE Trans Knowl Data Eng 18(11):1457\u20131466","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2654_CR42","doi-asserted-by":"crossref","unstructured":"Shi H, Li X (2011) A sentiment analysis model for hotel reviews based on supervised learning. In: 2011 International Conference on Machine Learning and Cybernetics, vol\u00a03, pp 950\u2013954","DOI":"10.1109\/ICMLC.2011.6016866"},{"key":"2654_CR43","doi-asserted-by":"crossref","unstructured":"Somya P Bansal, Ahmad T (2016) Methods and techniques of intrusion detection: a review. pp 518\u2013529, 10.1007\/978-981-10-3433-662","DOI":"10.1007\/978-981-10-3433-6_62"},{"key":"2654_CR44","unstructured":"Steffen J (2004) N-gram language modeling for robust multi-lingual document classification. In: Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC\u201904), European Language Resources Association (ELRA), Lisbon, Portugal, http:\/\/www.lrec-conf.org\/proceedings\/lrec2004\/pdf\/510.pdf"},{"key":"2654_CR45","doi-asserted-by":"crossref","unstructured":"Tang D, Wei F, Yang N, Zhou M, Liu T, Qin B (2014) Learning sentiment-specific word embedding for twitter sentiment classification. vol\u00a01, pp 1555\u20131565, 10.3115\/v1\/P14-1146","DOI":"10.3115\/v1\/P14-1146"},{"key":"2654_CR46","doi-asserted-by":"crossref","unstructured":"Tang D, Qin B, Liu T (2015) Document modeling with gated recurrent neural network for sentiment classification. In: Proceedings of the 2015 conference on empirical methods in natural language processing, pp 1422\u20131432","DOI":"10.18653\/v1\/D15-1167"},{"key":"2654_CR47","unstructured":"Trip Advisor (2018) 6 Tren Wisata Utama Tahun 2016. https:\/\/www.tripadvisor.co.id\/TripAdvisorInsights\/w665. Accessed 19 Feb 2020"},{"key":"2654_CR48","doi-asserted-by":"publisher","unstructured":"Umer M, Ashraf I, Mehmood A, Ullah DS, Choi GS (2020) Predicting numeric ratings for google apps using text features and ensemble learning. ETRI J. https:\/\/doi.org\/10.4218\/etrij.2019-0443","DOI":"10.4218\/etrij.2019-0443"},{"key":"2654_CR49","doi-asserted-by":"publisher","first-page":"156695","DOI":"10.1109\/ACCESS.2020.3019735","volume":"8","author":"M Umer","year":"2020","unstructured":"Umer M, Imtiaz Z, Ullah S, Mehmood A, Choi GS, On BW (2020) Fake news stance detection using deep learning architecture (cnn-lstm). IEEE Access 8:156695\u2013156706","journal-title":"IEEE Access"},{"key":"2654_CR50","doi-asserted-by":"publisher","first-page":"93782","DOI":"10.1109\/ACCESS.2020.2994810","volume":"8","author":"M Umer","year":"2020","unstructured":"Umer M, Sadiq S, Ahmad M, Ullah S, Choi GS, Mehmood A (2020) A novel stacked cnn for malarial parasite detection in thin blood smear images. IEEE Access 8:93782\u201393792","journal-title":"IEEE Access"},{"key":"2654_CR51","unstructured":"Wan Y, Nakayama M (2014) The reliability of online review helpfulness. J Electron Commer Res 15"},{"key":"2654_CR52","doi-asserted-by":"crossref","unstructured":"Wang D, Zhu S, Li T (2013) Sumview: A web-based engine for summarizing product reviews and customer opinions. Expert Syst Appl 40(1):27\u201333. 10.1016\/j.eswa.2012.05.070, http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417412007865","DOI":"10.1016\/j.eswa.2012.05.070"},{"key":"2654_CR53","doi-asserted-by":"publisher","unstructured":"Yamunadevi M, Ranjani S (2020) Efficient segmentation of the lung carcinoma by adaptive fuzzy-glcm (af-glcm) with deep learning based classification. J Ambient Intell Human Comput. https:\/\/doi.org\/10.1007\/s12652-020-01874-7","DOI":"10.1007\/s12652-020-01874-7"},{"key":"2654_CR54","doi-asserted-by":"publisher","first-page":"59618","DOI":"10.1109\/ACCESS.2018.2872730","volume":"6","author":"L Yang","year":"2018","unstructured":"Yang L, Zheng Y, Cai X, Dai H, Mu D, Guo L, Dai T (2018) A lstm based model for personalized context-aware citation recommendation. IEEE Access 6:59618\u201359627","journal-title":"IEEE Access"},{"key":"2654_CR55","unstructured":"Yin W, Kann K, Yu M, Sch\u00fctze H (2017) Comparative study of CNN and RNN for natural language processing. CoRR abs\/1702.01923, http:\/\/arxiv.org\/abs\/1702.01923,"},{"key":"2654_CR56","doi-asserted-by":"crossref","unstructured":"Zadrozny B, Elkan C (2002) Transforming classifier scores into accurate multiclass probability estimates. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 10(1145\/775047):775151","DOI":"10.1145\/775047.775151"},{"key":"2654_CR57","first-page":"267","volume":"15","author":"L Zhu","year":"2014","unstructured":"Zhu L, Yin G, He W (2014) Is this opinion leader\u2019s review useful? peripheral cues for online review helpfulness. J Electron Commer Res 15:267\u2013280","journal-title":"J Electron Commer Res"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-020-02654-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-020-02654-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-020-02654-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T19:40:35Z","timestamp":1630438835000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-020-02654-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,8]]},"references-count":57,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2021,10]]}},"alternative-id":["2654"],"URL":"https:\/\/doi.org\/10.1007\/s12652-020-02654-z","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,8]]},"assertion":[{"value":"7 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 October 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 November 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"\u201dThe authors declare no conflict of interest. The funding agency had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results\u201d.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest"}}]}}